/*
 * Copyright 2009 ZXing authors
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

/*namespace com.google.zxing.common {*/

import Binarizer from './../Binarizer'
import LuminanceSource from './../LuminanceSource'
import BitArray from './BitArray'
import BitMatrix from './BitMatrix'
import Exception from './../Exception'

/**
 * This Binarizer implementation uses the old ZXing global histogram approach. It is suitable
 * for low-end mobile devices which don't have enough CPU or memory to use a local thresholding
 * algorithm. However, because it picks a global black point, it cannot handle difficult shadows
 * and gradients.
 *
 * Faster mobile devices and all desktop applications should probably use HybridBinarizer instead.
 *
 * @author dswitkin@google.com (Daniel Switkin)
 * @author Sean Owen
 */
export default class GlobalHistogramBinarizer extends Binarizer {

  private static LUMINANCE_BITS = 5;
  private static LUMINANCE_SHIFT = 8 - GlobalHistogramBinarizer.LUMINANCE_BITS;
  private static LUMINANCE_BUCKETS = 1 << GlobalHistogramBinarizer.LUMINANCE_BITS;
  private static EMPTY = Uint8ClampedArray.from([0]);

  private luminances: Uint8ClampedArray
  private buckets: Int32Array

  public constructor(source: LuminanceSource) {
    super(source)
    this.luminances = GlobalHistogramBinarizer.EMPTY
    this.buckets = new Int32Array(GlobalHistogramBinarizer.LUMINANCE_BUCKETS)
  }

  // Applies simple sharpening to the row data to improve performance of the 1D Readers.
  /*@Override*/
  public getBlackRow(y: number /*int*/, row: BitArray): BitArray /*throws NotFoundException*/ {
    const source = this.getLuminanceSource()
    const width = source.getWidth();
    if (row === undefined || row === null || row.getSize() < width) {
      row = new BitArray(width)
    } else {
      row.clear()
    }

    this.initArrays(width)
    const localLuminances = source.getRow(y, this.luminances)
    const localBuckets = this.buckets
    for (let x = 0; x < width; x++) {
      localBuckets[(localLuminances[x] & 0xff) >> GlobalHistogramBinarizer.LUMINANCE_SHIFT]++
    }
    const blackPoint = GlobalHistogramBinarizer.estimateBlackPoint(localBuckets)

    if (width < 3) {
      // Special case for very small images
      for (let x = 0; x < width; x++) {
        if ((localLuminances[x] & 0xff) < blackPoint) {
          row.set(x)
        }
      }
    } else {
      let left = localLuminances[0] & 0xff
      let center = localLuminances[1] & 0xff
      for (let x = 1; x < width - 1; x++) {
        const right = localLuminances[x + 1] & 0xff
        // A simple -1 4 -1 box filter with a weight of 2.
        if (((center * 4) - left - right) / 2 < blackPoint) {
          row.set(x)
        }
        left = center
        center = right
      }
    }
    return row
  }

  // Does not sharpen the data, as this call is intended to only be used by 2D Readers.
  /*@Override*/
  public getBlackMatrix(): BitMatrix /*throws NotFoundException*/ {
    const source = this.getLuminanceSource()
    const width = source.getWidth()
    const height = source.getHeight()
    const matrix = new BitMatrix(width, height)

    // Quickly calculates the histogram by sampling four rows from the image. This proved to be
    // more robust on the blackbox tests than sampling a diagonal as we used to do.
    this.initArrays(width)
    const localBuckets = this.buckets
    for (let y = 1; y < 5; y++) {
      const row = height * y / 5;
      const localLuminances = source.getRow(row, this.luminances)
      const right = Math.floor((width * 4) / 5)
      for (let x = Math.floor(width / 5); x < right; x++) {
        const pixel = localLuminances[x] & 0xff
        localBuckets[pixel >> GlobalHistogramBinarizer.LUMINANCE_SHIFT]++
      }
    }
    const blackPoint = GlobalHistogramBinarizer.estimateBlackPoint(localBuckets)

    // We delay reading the entire image luminance until the black point estimation succeeds.
    // Although we end up reading four rows twice, it is consistent with our motto of
    // "fail quickly" which is necessary for continuous scanning.
    const localLuminances = source.getMatrix()
    for (let y = 0; y < height; y++) {
      const offset = y * width;
      for (let x = 0; x < width; x++) {
        const pixel = localLuminances[offset + x] & 0xff
        if (pixel < blackPoint) {
          matrix.set(x, y)
        }
      }
    }

    return matrix
  }

  /*@Override*/
  public createBinarizer(source: LuminanceSource): Binarizer {
    return new GlobalHistogramBinarizer(source)
  }

  private initArrays(luminanceSize: number /*int*/): void {
    if (this.luminances.length < luminanceSize) {
      this.luminances = new Uint8ClampedArray(luminanceSize)
    }
    const buckets = this.buckets
    for (let x = 0; x < GlobalHistogramBinarizer.LUMINANCE_BUCKETS; x++) {
      buckets[x] = 0
    }
  }

  private static estimateBlackPoint(buckets: Int32Array): number /*int*/ /*throws NotFoundException*/ {
    // Find the tallest peak in the histogram.
    const numBuckets = buckets.length
    let maxBucketCount = 0
    let firstPeak = 0
    let firstPeakSize = 0
    for (let x = 0; x < numBuckets; x++) {
      if (buckets[x] > firstPeakSize) {
        firstPeak = x
        firstPeakSize = buckets[x]
      }
      if (buckets[x] > maxBucketCount) {
        maxBucketCount = buckets[x]
      }
    }

    // Find the second-tallest peak which is somewhat far from the tallest peak.
    let secondPeak = 0
    let secondPeakScore = 0
    for (let x = 0; x < numBuckets; x++) {
      const distanceToBiggest = x - firstPeak
      // Encourage more distant second peaks by multiplying by square of distance.
      const score = buckets[x] * distanceToBiggest * distanceToBiggest;
      if (score > secondPeakScore) {
        secondPeak = x
        secondPeakScore = score
      }
    }

    // Make sure firstPeak corresponds to the black peak.
    if (firstPeak > secondPeak) {
      const temp = firstPeak
      firstPeak = secondPeak
      secondPeak = temp
    }

    // If there is too little contrast in the image to pick a meaningful black point, throw rather
    // than waste time trying to decode the image, and risk false positives.
    if (secondPeak - firstPeak <= numBuckets / 16) {
      throw new Exception(Exception.NotFoundException)
    }

    // Find a valley between them that is low and closer to the white peak.
    let bestValley = secondPeak - 1
    let bestValleyScore = -1
    for (let x = secondPeak - 1; x > firstPeak; x--) {
      const fromFirst = x - firstPeak
      const score = fromFirst * fromFirst * (secondPeak - x) * (maxBucketCount - buckets[x]);
      if (score > bestValleyScore) {
        bestValley = x
        bestValleyScore = score
      }
    }

    return bestValley << GlobalHistogramBinarizer.LUMINANCE_SHIFT
  }

}
